This invention relates to techniques for extracting data from a data source in a first format, and translating the extracted data into a second format.
Laboratory data management systems such as LIMS and ELN systems can significantly increase the efficiency and productivity of experimental research by integrating experimental data across different projects, sites and technologies. Providing an integrated database of an organization's aggregated research information that can be searched and analyzed can improve decision-making and collaboration within and across project teams and departments, and can facilitate regulatory compliance.
A typical research organization may rely on experimental data from a wide variety of sources. Thus, for example, during the development of a typical drug product, researchers may generate characterization and screening data by any number of techniques, including chromatography (e.g., GC, HPLC), spectroscopy (e.g., FTIR, NIR, UV-Vis, NMR), microscopy (e.g., optical, SEM, TEM), particle size measurement, X-ray diffraction, and the like, as well as product data, such as product yields, purity and impurity profiles for starting materials, intermediates, and drug candidates, dissolution studies, and chemical stability measurements for drug candidates and excipients.
In the past, researchers have stored this information in many different locations, including paper laboratory notebooks, reports, network drives (in the case of analytical data, often readable only with the required software), and LIMS. To make all of this disparate data available in a single, integrated data management system, the data must first be translated from its native format into a common format that provides the structure necessary for integrated storage, search and analysis.